Method and system for detecting a relevant utterance in a voice session

ABSTRACT

A method and apparatus for detecting use of an utterance. A voice session including voice signals generated during a conversation between a first participant and a second participant is monitored by a speech analytics processor. The speech analytics processor detects the use of an utterance. A speech recognition processor channel selected from a pool of speech recognition processor channels and is coupled to the voice session. The speech recognition processor provided speech recognition services to a voice-enabled application. The speech recognition processor channel is then decoupled from the voice session. The speech analytics processor continues to monitor the conversation for subsequent use of the utterance.

FIELD OF THE INVENTION

The present invention relates generally to speech recognitionprocessing, and in particular to providing speech recognition processingin response to detection of an utterance.

BACKGROUND OF THE INVENTION

A speech recognition processor uses a predefined grammar to detect wordsin speech. Speech recognition processors are frequently used as a frontend to provide voice-enabled command and control applications. A speechrecognition processor detects a word match relatively quickly, but thewords that can be detected are limited to the words associated with theparticular grammar. Speech recognition processors are typically noteffective at or designed to detect a particular relevant word orutterance in an unbounded stream of largely irrelevant words orutterances spoken at a conventional speaking rate, as might occur duringa conversation between two or more participants. Rather, a speechrecognition processor typically requires a speaker to speak quitedistinctly and with brief pauses between commands, because the speechrecognition processor is attempting to process each separate utteranceas a command. In the context of a normal conversation, coupling a speechrecognition channel to the conversation would result in the speechrecognition processor attempting to determine whether each spoken wordmatched a word in the predefined grammar, and responding with errorindicators or false positive results for each word that did not match.Speech recognition processors require significant memory and processingcapabilities, and in commercial settings are frequently implemented instand-alone devices that can handle speech processing requirements for afinite number of voice sessions concurrently.

Many speech-enabled applications are front-ends to customer servicesystems that offer full-time availability, and thus use dedicated speechrecognition processors. For example, many businesses now require acaller seeking customer service to interact with a voice-enabledapplication that will ask for information such as an account number andzip code, and in response provide information about the caller'saccount, before allowing the caller to speak to a human.Telecommunications providers are beginning to develop ‘on-demand’voice-enabled applications that can be initiated by a participant in aconversation on an impromptu basis. For example, a telecommunicationsprovider may desire to provide a subscriber the ability, at any time, torequest that a third-party be invited to be joined to an existing callvia a speech-enabled application. Currently, such an on-demandvoice-enabled application would require that a speech recognitionprocessor channel be dedicated to a voice session for the entire voicesession. Because speech recognition processors are memory and processorintensive, it may be impractical or cost-prohibitive to simultaneouslyprovide hundreds or even thousands of speech recognition processingchannels during hundreds or thousands of voice sessions. Moreover,because speech recognition processors are not designed to select aparticular relevant word out of a stream of mainly irrelevant wordsoccurring at a conventional speaking rate, the speech recognitionprocessor would attempt to match each irrelevant word during theconversation to a predefined grammar of commands. Since the majority ofwords spoken in the conversation would not match any commands in thepredefined grammar, the speech recognition processor would repeatedlyrespond with error indicators or false positive results for each wordthat did not match. Thus, currently there are several problems withusing speech recognition processors in on-demand voice-enabledapplications.

Speech analytic processors, in contrast to speech recognitionprocessors, are used to search for utterances, such as words or othersounds, in large quantities of recorded voice data. Speech analyticprocessors are not typically employed in real-time applications. Aspeech analytic processor typically receives a recorded voice session asinput and encodes the recorded voice session into a searchable file, ordatabase. The speech analytic processor, or associated query module, canthen search for and detect designated sounds that may appear in thedatabase. Speech analytics processors do not utilize a grammar and arecapable of searching for any designated word, phrase, or sound once thedatabase is generated and, in response to a search request, provide atime offset within the recorded voice session where such word, phrase,or sound was spoken. Speech analytics processors are extremely fast andbecause they are not designed to be used in a real-time environment orrecognize complicated grammars, and they use significantly lessprocessor and memory resources than a speech recognition processor.

To minimize costs associated with speech recognition processing, itwould be beneficial if a speech recognition processor could beselectively allocated to a voice session after a determination has beenmade that a participant in the voice session desires a voice-enabledapplication, rather than dedicate a speech recognition processor to thevoice session that may not be used during the voice session. If a speechrecognition processor could be allocated on an impromptu basis, arelatively small pool of speech recognition processors could be used tosupport a relatively large number of voice sessions. It would be furtherbeneficial if a speech analytics processor could be used to determinewhen a participant in a voice session desires an on-demandspeech-enabled application, because speech analytics processors requiresignificantly less resources than speech recognition processors.

SUMMARY OF THE INVENTION

The present invention uses a speech analytics processor to monitor aconversation for the use of an utterance, such as a hot word. Upondetection of the hot word, a speech recognition processor beginsmonitoring the conversation for the use of a command associated with avoice-enabled application. The speech recognition processor communicateswith the voice-enabled application to provide the voice-enabledapplication information associated with commands spoken by a participantin the conversation. After the participant is finished using thevoice-enabled application, the speech analytics processor continues tomonitor the conversation for use of the hot word, and the speechrecognition processor is decoupled from the conversation and isavailable for use by other voice sessions.

According to one embodiment of the invention, a voice session is encodedin a media stream comprising voice signals of the participants of theconversation. A speech analytics processor monitors the voice signalsfor use of an utterance spoken by a participant in the conversation toinvoke a speech-enabled application. Upon detection of the utterance,the voice session is coupled to one of a pool of speech recognitionprocessor channels. After the voice-enabled application is completed,the speech recognition processor channel is decoupled from the voicesession and returned to the pool of speech recognition processorchannels. The present invention enables a relatively small pool ofspeech recognition processors to be used for a relatively large numberof voice sessions that may require an on-demand voice-enabledapplication on an impromptu basis.

According to another embodiment of the invention, a voice sessioncarrying a conversation between first and second participants isprovided to a media application server that provides one or moreon-demand voice-enabled applications to the participants in theconversation. The voice session is monitored by a speech analyticsprocessor running on the media application server. During theconversation, the first participant desires to invite a thirdparticipant to the voice session. The first participant speaks a hotword, the speech analytics processor detects the use of the hot word,and the of speech analytics processor notifies a control systemassociated with the media application server thereof. The mediaapplication server is coupled to a speech recognition processor having aplurality of speech recognition processor channels. The mediaapplication server obtains a speech recognition processor channel fromthe pool of speech recognition processor channels, and couples thespeech recognition processor channel to the voice session. Thevoice-enabled application provides the speech recognition processor agrammar for recognizing available commands that may be spoken by theparticipant. The speech recognition processor awaits a command spoken bythe participant. Upon recognizing a command, the speech recognitionprocessor provides the speech-enabled application the recognizedcommand. The speech-enabled application determines that the commandrelates to initiating a voice session to a third party and joining thecall with the existing voice session. The speech-enabled applicationinitiates a call to the third party, joins the call to the existingvoice session, and informs the control system that the speechrecognition processor channel may be returned to the pool of speechrecognition processor channels. The control system returns the speechrecognition processor channel to the pool of speech recognitionprocessor channels. The control system couples the voice session, nowhaving three participants, to the speech analytics processor formonitoring for subsequent use of the hot word by one of the participantsof the conversation.

Those skilled in the art will appreciate the scope of the presentinvention and realize additional aspects thereof after reading thefollowing detailed description of the preferred embodiments inassociation with the accompanying drawing figures.

BRIEF DESCRIPTION OF THE DRAWINGS FIGURES

The accompanying drawing figures incorporated in and forming a part ofthis specification illustrate several aspects of the invention, andtogether with the description serve to explain the principles of theinvention.

FIG. 1 is a block diagram illustrating modules for implementing oneembodiment of the present invention.

FIG. 2 is a flow chart illustrating a process for detecting an utteranceduring a conversation and providing a speech recognition processorchannel for an on-demand voice-enabled application according to oneembodiment of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The embodiments set forth below represent the necessary information toenable those skilled in the art to practice the invention and illustratethe best mode of practicing the invention. Upon reading the followingdescription in light of the accompanying drawing figures, those skilledin the art will understand the concepts of the invention and willrecognize applications of these concepts not particularly addressedherein. It should be understood that these concepts and applicationsfall within the scope of the disclosure and the accompanying claims.

The present invention relates to selective use of a speech recognitionprocessor. The present invention enables, among other advantages,providing on-demand voice-enabled applications that may be used on animpromptu basis without requiring that a relatively expensive andprocessor intensive speech recognition processing channel be allocatedto a conversation during the entire duration of the conversation.Through the use of the present invention, a relatively small pool ofspeech recognition processing channels can be used to support arelatively large number of voice sessions, reducing both capitalequipment expenditures and licensing fees associated with speechrecognition processing channels and providing a participant in aconversation the ability to invoke the on-demand voice-enabledapplication while speaking at a conventional speaking rate.

FIG. 1 is a block diagram illustrating modules for implementing oneembodiment of the present invention. A media application server (MAS) 10includes a control system 12 that includes a memory 14. The MAS 10 canbe a conventional or proprietary computing device, such as a computer ortelecommunications server, that includes a processor capable ofexecuting the control system 12. The control system 12 can include aconventional or proprietary operating system and additional software andhardware suitable for providing conventional operating system andtelecommunications functions, such as memory management, input/outputfunctions, and the like, as well as additional functionality asdescribed herein. The MAS 10 also includes a communications interface 16that is coupled to one or more telecommunications devices 18, such as acall server 18A, a private branch exchange (PBX) 18B, a SessionInitiation Protocol (SIP)/Public Switched Telephone Network (PSTN)gateway 18C, and the like. Participants 24 use user devices 26 to engagein conversations with one another. The user devices 26 can comprise anysuitable communications devices, such as wired, cordless, or cellulartelephones, computers, personal digital assistants, and the like. Theconversations between respective pairs of participants, such as theparticipants 24A, 24B, are established by one or more of the respectivetelecommunication devices 18 as a voice session, and are representedherein by voice sessions 28A, 28B, 28C. Mechanisms for setting up andtearing down voice sessions, such as the voice sessions 28A, 28B, 28C,are well known to those skilled in the art and will not be discussedherein. For purposes of illustration the voice sessions 28A, 28B, 28Cmay be referred to herein collectively as the voice sessions 28 wherethe discussion does not relate to a particular voice session 28A, 28B,or 28C.

The telecommunications devices 18 are capable of providing one or morevoice sessions 28 to the MAS 10 for desired processing. The MAS 10includes a voice-enabled application 30 that may provide functionalityto a participant 24 during a voice session 28. The voice-enabledapplication 30 may be an ‘on-demand’ application. For example, thevoice-enabled application 30 may not provide functionality until calledupon by a participant 24 to do so. After being initiated or otherwisenotified by a participant 24 that the participant 24 desires a servicefrom the voice-enabled application 30, the voice-enabled application 30interacts with a speech recognition processor 32 to enable theparticipant 24 to interact with the voice-enabled application 30 viaspeech commands. The speech recognition processor 32 provides speechrecognition services to one or more voice-enabled applications 30 viaspeech recognition channels 34A-34D, one of which is allocated to arespective voice-enabled application 30 as needed.

Speech recognition processors, such as the speech recognition processor32, are processor and memory intensive devices that utilize a definedgrammar having a finite vocabulary of commands and attempt to detect theuse of a command in speech in real-time. Speech recognition is aspecialized technology that is frequently provided to a business by athird party that specializes in speech recognition technology. In acommercial environment, speech recognition processors are typicallydedicated servers that work in conjunction with a specific applicationto provide an integrated voice-enabled application, or that provide afinite number of speech recognition channels for use however thebusiness desires. Speech recognition processors are frequently licensedfor use on a per channel basis, and in practice, licensing fees andequipment investment necessary to provide a speech recognition channelfor a large number of voice sessions 28 is cost prohibitive. Moreover,speech recognition processors specialize in recognizing a finite numberof commands and are significantly more accurate in detecting the use ofa command when words are spoken slowly, distinctly, and with pausesbetween each word. Using a speech recognition processor to detect asingle word or utterance in a stream of words would cause the speechrecognition processor to attempt to match each separate word orutterance to the predefined grammar, and repeatedly respond with errorindicators or false positive results for each word or utterance that didnot match the predefined grammar.

The MAS 10 also includes an embedded speech analytics processor 36. Byembedded, it is intended that the speech analytics processor 36 canexecute on the same processor as other applications in the MAS 10.Alternately, the speech analytics processor 36 can be executed on aseparate device and be coupled to the MAS 10 via a network. Speechanalytic processors are designed to find occurrences of designatedutterances, such as words, phrases, or other sounds, in large quantitiesof voice data. The process of speech analytics is sometimes referred toas data mining, and can be used, for example, by a government agency todetermine if certain words were spoken during, for example, anyinternational call that was placed on a particular day. A speechanalytics processor typically receives voice signals associated with aconversation as input and encodes the voice signals into a searchabledatabase or file. A query module can then be used to determine whetherone or more words or phrases are present in the searchable database. Oneparticular example of speech analytics software is provided by NexidiaInc., 3565 Piedmont Road NE, Building Two, Suite 400, Atlanta, Ga.30305, and its white paper entitled Phonetic Search Technology, 2007 andthe references cited therein, wherein the white paper and citedreferences are each incorporated herein by reference in theirentireties. Generally, the Nexidia speech analytics processor encodesvoice signals as phonemes, and creates a phoneme-based index of theconversation. A query including a query term comprising one or morewords is entered, the query term is similarly encoded as phonemes, andthe phoneme-based index is used to determine if the query term ispresent in the searchable database. If so, the speech analyticsprocessor can return a time offset indicating where in the voice signalsthe query term is present.

Unlike a speech recognition processor, a speech analytics processor isnot designed to work with a complex grammar or react to a predeterminednumber of commands in real-time. Consequently, speech analyticsprocessors use significantly less processor and memory than a speechrecognition processor. However, speech analytics processors are verygood at finding a particular utterance in a recorded conversation spokenat a conventional speaking rate. The present invention uses a speechanalytics processor 36 to monitor a conversation and detect anutterance, such as a hot word, in a near real-time time frame. Thedrawings and examples provided herein will refer to the utterance as ahot word, but those skilled in the art will appreciate that theinvention is not limited to detecting a hot word, and can be used todetect any utterance, whether it be a word, a combination of words, orother sounds. The present invention interfaces with the speech analyticsprocessor 36 and provides the speech analytics processor 36 segments ofspeech as they are generated by the participants in the conversation.The precise method for providing the speech analytics processor 36 canvary depending on the particular speech analytics processor 36 used but,according to one embodiment of the invention, the speech analyticsprocessor 36 provides an application programming interface (API) thatcan be called by the control system 12 to provide segments of speech tothe speech analytics processor 36.

The speech analytics processor 36 processes the speech segments anddetermines whether the hot word is located in the speech segment. Upondetection of the hot word, the speech analytics processor 36 notifiesthe control system 12, which in turn interacts with the voice-enabledapplication 30. A speech recognition channel 34 is obtained from a poolof the speech recognition channels 34A-34D, and is coupled to therespective voice session 28 in which the hot word was detected. Thespeech recognition processor 32 provides voice recognition services tothe voice-enabled application 30. After the voice-enabled application 30has provided the desired function to the participants 24, the speechrecognition channel 34 is returned to the pool of speech recognitionchannels 34A-34D. The voice session 28 continues to be monitored forsubsequent use of the hot word by the speech analytics processor 36.

FIG. 2 is a flowchart providing an example of hot word detectionaccording to one embodiment of the present invention. For purposes ofillustration, FIG. 2 will be discussed in conjunction with FIG. 1.Assume that the participant 24A and the participant 24B engage in aconversation. The voice session 28A is established between the userdevices 26A and 26B by one or more telecommunications devices 18. Voicesignals of the participants 24A, 24B are provided in a media stream fromthe respective telecommunications devices 18 to the MAS 10. The speechanalytics processor 36 receives the media stream of voice signals andmonitors the conversation for the use of a predetermined hot word (step100). The predetermined hot word can be any desired word or combinationof words that a participant 24 may use to initiate, invoke, or otherwiseestablish communications with the voice-enabled application 30.Preferably, the predetermined hot word is a word or phrase that wouldnot normally arise in a conversation.

Assume that the participant 24B asks the participant 24A for a date ofcompletion of a project. The participant 24A responds to the participant24B indicating that the participant 24A cannot provide a completiondate; however, another individual would be able to provide a completiondate. The participant 24B suggests to the participant 24A that theyattempt to initiate a telephone call with the individual and conferencethe individual into the existing voice session 28A. The participant 24Bspeaks the desired hot word, for example, ‘personal agent.’ The speechanalytics processor 36, in conjunction with the control system 12, iscontinually monitoring the voice session 28A, encoding the voice signalsinto encoded segments of a predetermined size, and searching the encodedsegments for an occurrence of the hot word. The speech analyticsprocessor 36 detects the use of the hot word in the media stream (step102). The speech analytics processor 36 indicates to the control system12 that the hot word was detected associated with the voice session 28A(step 104). The control system 12 decouples the voice session 28A fromthe speech analytics processor 36 (step 106).

The control system 12 interfaces with the speech recognition processor32 to obtain a speech recognition channel 34 from the pool of speechrecognition channels 34A-34D. The control system 12 couples the speechrecognition channel 34 to the voice session 28A (step 108). The controlsystem 12 also initiates the voice-enabled application 30, whichprovides a grammar to the speech recognition processor 32 for use by theparticipants 24A, 24B (step 110). Alternately, the voice-enabledapplication 30 may be initiated at the initial establishment of thevoice session 28A, and upon initiation may provide the predetermined hotword to the control system 12 for monitoring. The participant 24B isprompted for a command. The participant 24B speaks a predeterminedcommand that is recognized by the speech recognition processor 32 and ispassed to the voice-enabled application 30, which in turn initiates acall to the individual. The voice-enabled application 30, upon reachingthe individual, joins the call to the voice session 28A (step 112). Thevoice-enabled application 30 indicates to the control system 12 that thevoice-enabled application 30 is finished. The control system 12decouples the voice session 28A from the speech recognition channel 34(step 114). The control system 12 re-couples the speech analyticsprocessor 36 to the voice session 28A for continued monitoring of theconversation for subsequent use of the hot word by one of theparticipants 24 (step 116).

The present invention thus provides a mechanism for sharing a relativelysmall number of speech recognition processing channels among arelatively large number of voice sessions to provide speech-enabledapplications for each voice session. The present invention reducescapital equipment costs and licensing fees associated with thecommercial use of speech recognition processors.

Those skilled in the art will recognize improvements and modificationsto the preferred embodiments of the present invention. All suchimprovements and modifications are considered within the scope of theconcepts disclosed herein and the claims that follow.

What is claimed is:
 1. A method for monitoring a conversationcomprising: coupling a voice session comprising voice signals generatedduring a conversation between a first participant and a secondparticipant to a speech analytics processor to detect in the voicesignals a use of an utterance requesting a service from a voice enabledapplication; receiving from the speech analytics processor an indicationthat the utterance has been detected in the voice signals and decouplingthe speech analytics processor from the voice session; coupling thevoice session to a speech recognition processor which receives a grammarcomprising a plurality of commands for the voice enabled application,wherein the speech recognition processor monitors the voice sessionsubsequent to the use of the utterance for one of the plurality ofcommands; and receiving from the speech recognition processor anindication that the one of the plurality of commands has been detectedand re-coupling the speech analytics processor to the voice session. 2.The method of claim 1 wherein coupling the speech analytics processor todetect in the voice signals the use of the utterance further comprisesgenerating, by the speech analytics processor, a phonetic indexcomprising phonemes associated with the voice signals, and determiningif one or more phonemes in the phonetic index matches one or morephonemes associated with the utterance.
 3. The method of claim 1 whereincoupling the voice session to the speech recognition processor furthercomprises coupling the voice session to the speech recognition processorafter the utterance has been detected.
 4. The method of claim 3 furthercomprising decoupling the speech recognition processor from the voicesession.
 5. The method of claim 3 wherein coupling the voice session tothe speech recognition processor comprises coupling the voice session toone of a plurality of speech recognition channels associated with a poolof speech recognition channels, and wherein the one of the plurality ofspeech recognition channels is selected from the pool of speechrecognition channels upon detecting the use of the utterance, and theone of the plurality of speech recognition channels is returned to thepool of speech recognition channels upon decoupling the one of theplurality of speech recognition channels from the voice session.
 6. Themethod of claim 1 wherein the speech analytics processor stores asegment of the voice signals in a first memory, reduces the voicesignals in the segment to a plurality of phonemes, and searches theplurality of phonemes to determine if any of the plurality of phonemesmatch a second plurality of phonemes associated with the utterance. 7.The method of claim 1 further comprising notifying, upon detecting theutterance, a voice-enabled application of the use of the utterance. 8.An apparatus for monitoring a conversation comprising: a communicationsinterface adapted to interface with a telecommunications device; and acontrol system coupled to the communications interface and adapted to:couple a voice session comprising voice signals generated during aconversation between a first participant and a second participant to aspeech analytics processor to detect in the voice signals a use of anutterance requesting a service from a voice enabled application; receivefrom the speech analytics processor an indication that the utterance hasbeen detected in the voice signals and decouple the speech analyticsprocessor from the voice session; couple the voice session to a speechrecognition processor which receives a grammar comprising a plurality ofcommands for the voice enabled application, wherein the speechrecognition processor monitors a media stream subsequent to the use ofthe utterance for one of the plurality of commands; and receive from thespeech recognition processor an indication that the one of the pluralityof commands has been detected and re-couple the speech analyticsprocessor to the voice session.
 9. The apparatus of claim 8 wherein thespeech analytics processor is further adapted to generate a phoneticindex comprising phonemes associated with the voice signals, anddetermine if one or more phonemes in the phonetic index matches one ormore phonemes associated with the utterance.
 10. The apparatus of claim8 wherein to couple the media stream to the speech recognition processorthe control system is further adapted to couple the voice session to thespeech recognition processor after the utterance has been detected. 11.The apparatus of claim 10 wherein the control system is further adaptedto decouple the speech recognition processor from the voice session. 12.The apparatus of claim 10 wherein to couple the voice session to thespeech recognition processor the control system is further adapted tocouple the voice session to one of a plurality of speech recognitionchannels associated with a pool of speech recognition channels, andwherein the one of the plurality of speech recognition channels isselected from the pool of speech recognition channels upon detecting theuse of the utterance, and the one of the plurality of speech recognitionchannels is returned to the pool of speech recognition channels upondecoupling the one of the plurality of speech recognition channels fromthe voice session.
 13. The apparatus of claim 8 wherein the speechanalytics processor is adapted to store a segment of the voice signalsin a first memory, reduce the voice signals in the segment to aplurality of phonemes, and search the plurality of phonemes to determineif any of the plurality of phonemes match a second plurality of phonemesassociated with the utterance.
 14. The apparatus of claim 8 wherein thecontrol system is further adapted to notify a voice-enabled applicationof the use of the utterance.
 15. A non-transitory computer-usable mediumhaving computer-readable instructions stored thereon for execution by aprocessor to perform a method comprising: coupling a voice sessioncomprising voice signals generated during a conversation between a firstparticipant and a second participant to a speech analytics processor todetect in the voice signals a use of an utterance requesting a servicefrom a voice enabled application; receiving from the speech analyticsprocessor an indication that the utterance has been detected in thevoice signals and decoupling the speech analytics processor from thevoice session; coupling the voice session to a speech recognitionprocessor which receives a grammar comprising a plurality of commandsfor the voice enabled application, wherein the speech recognitionprocessor monitors the voice session subsequent to the use of theutterance for one of the plurality of commands; and receiving from thespeech recognition processor an indication that the one of the pluralityof commands has been detected and re-coupling the speech analyticsprocessor to the voice session.
 16. The computer-usable medium of claim15 wherein the method further comprises coupling the speech analyticsprocessor to detect in the voice signals the use of the utterancefurther comprises generating, by the speech analytics processor, aphonetic index comprising phonemes associated with the voice signals,and determining if one or more phonemes in the phonetic index matchesone or more phonemes associated with the utterance.
 17. Thecomputer-usable medium of claim 15 wherein coupling the voice session tothe speech recognition processor further comprises coupling the voicesession to the speech recognition processor after the utterance has beendetected.
 18. The computer-usable medium of claim 15 wherein the methodfurther comprises decoupling the speech recognition processor from thevoice session.
 19. The computer-usable medium of claim 15 whereincoupling the voice session to the speech recognition processor comprisescoupling the voice session to one of a plurality of speech recognitionchannels associated with a pool of speech recognition channels, andwherein the one of the plurality of speech recognition channels isselected from the pool of speech recognition channels upon detecting theuse of the utterance, and the one of the plurality of speech recognitionchannels is returned to the pool of speech recognition channels upondecoupling the one of the plurality of speech recognition channels fromthe voice session.
 20. The computer-usable medium of claim 15 whereinthe method further comprises notifying, upon detecting the utterance, avoice-enabled application of the use of the utterance.